WEEK 6 · Sun, Oct 18, 12:00 PM CDT

Chicago Bears @ Atlanta Falcons

13 qualified model plays · 8 modeled lines did not qualify · 11-2-0

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MODEL OVERVIEW

What the board is seeing

Qualified plays 13 Published sides that cleared the current model thresholds.

Avg model win 69.3% Average estimated win probability across this game's qualified plays.

Avg no-vig edge +19.1% Model probability minus the market's no-vig implied probability.

Avg model-implied EV +30.3% Average modeled return using the published side price.

Projection gap is the raw difference between PDR's projection and the sportsbook line. No-vig edge is the probability advantage after removing sportsbook hold. They answer different questions.

How the model works →

QUALIFIED PLAYS

Game prop board

Ranked by the frozen published model board.

#1 MODEL PLAY

Kyle Pitts

Receptions

WIN

OVER 2.5

fanduel -146

Projection 5.3

Proj. gap +2.8

Model win 86.4%

No-vig market 55.5%

No-vig edge +31.0%

Model-implied EV +45.7%

WHY THIS PLAY

Projection 5.3 is 2.8 above the 2.5 line.

Model win probability 86.4% vs 55.5% no-vig market probability creates a +31.0% edge.

Qualified with 2154 residual samples, 86.4% model win, +31.0% no-vig edge, and +45.7% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 5 receptions

#2 MODEL PLAY

Drake London

Receptions

WIN

UNDER 6.5

fanduel -166

Projection 5.2

Proj. gap -1.3

Model win 80.3%

No-vig market 58.3%

No-vig edge +22.0%

Model-implied EV +28.6%

WHY THIS PLAY

Projection 5.2 is 1.3 below the 6.5 line.

Model win probability 80.3% vs 58.3% no-vig market probability creates a +22.0% edge.

Qualified with 2154 residual samples, 80.3% model win, +22.0% no-vig edge, and +28.6% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 4 receptions

#3 MODEL PLAY

Drake London

Receiving yards

WIN

UNDER 88.5

fanduel -114

Projection 76.7

Proj. gap -11.8

Model win 77.1%

No-vig market 50.0%

No-vig edge +27.1%

Model-implied EV +44.7%

WHY THIS PLAY

Projection 76.7 is 11.8 below the 88.5 line.

Model win probability 77.1% vs 50.0% no-vig market probability creates a +27.1% edge.

Qualified with 2154 residual samples, 77.1% model win, +27.1% no-vig edge, and +44.7% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 62 receiving yards

#4 MODEL PLAY

Kyle Pitts

Receiving yards

WIN

OVER 26.5

fanduel -114

Projection 55.8

Proj. gap +29.3

Model win 77.0%

No-vig market 50.0%

No-vig edge +27.0%

Model-implied EV +44.6%

WHY THIS PLAY

Projection 55.8 is 29.3 above the 26.5 line.

Model win probability 77.0% vs 50.0% no-vig market probability creates a +27.0% edge.

Qualified with 2154 residual samples, 77.0% model win, +27.0% no-vig edge, and +44.6% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 60 receiving yards

#5 MODEL PLAY

Colston Loveland

Receiving yards

WIN

OVER 34.5

fanduel -114

Projection 61.6

Proj. gap +27.1

Model win 74.1%

No-vig market 50.0%

No-vig edge +24.1%

Model-implied EV +39.2%

WHY THIS PLAY

Projection 61.6 is 27.1 above the 34.5 line.

Model win probability 74.1% vs 50.0% no-vig market probability creates a +24.1% edge.

Qualified with 2154 residual samples, 74.1% model win, +24.1% no-vig edge, and +39.2% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 65 receiving yards

#6 MODEL PLAY

Cole Kmet

Receiving yards

LOSS

OVER 9.5

fanduel -114

Projection 35.5

Proj. gap +26.0

Model win 72.4%

No-vig market 50.0%

No-vig edge +22.4%

Model-implied EV +36.0%

WHY THIS PLAY

Projection 35.5 is 26.0 above the 9.5 line.

Model win probability 72.4% vs 50.0% no-vig market probability creates a +22.4% edge.

Qualified with 2154 residual samples, 72.4% model win, +22.4% no-vig edge, and +36.0% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 3 receiving yards

#7 MODEL PLAY

Jahan Dotson

Receptions

WIN

OVER 1.5

fanduel -162

Projection 3.3

Proj. gap +1.8

Model win 67.8%

No-vig market 57.9%

No-vig edge +9.9%

Model-implied EV +9.6%

WHY THIS PLAY

Projection 3.3 is 1.8 above the 1.5 line.

Model win probability 67.8% vs 57.9% no-vig market probability creates a +9.9% edge.

Qualified with 2154 residual samples, 67.8% model win, +9.9% no-vig edge, and +9.6% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 3 receptions

#8 MODEL PLAY

Colston Loveland

Receptions

WIN

OVER 3.5

fanduel +108

Projection 5.1

Proj. gap +1.6

Model win 65.8%

No-vig market 44.9%

No-vig edge +20.9%

Model-implied EV +36.9%

WHY THIS PLAY

Projection 5.1 is 1.6 above the 3.5 line.

Model win probability 65.8% vs 44.9% no-vig market probability creates a +20.9% edge.

Qualified with 2154 residual samples, 65.8% model win, +20.9% no-vig edge, and +36.9% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 6 receptions

#9 MODEL PLAY

Cole Kmet

Receptions

WIN

OVER 1.5

fanduel +162

Projection 3.0

Proj. gap +1.5

Model win 62.1%

No-vig market 35.7%

No-vig edge +26.4%

Model-implied EV +62.6%

WHY THIS PLAY

Projection 3.0 is 1.5 above the 1.5 line.

Model win probability 62.1% vs 35.7% no-vig market probability creates a +26.4% edge.

Qualified with 2154 residual samples, 62.1% model win, +26.4% no-vig edge, and +62.6% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 2 receptions

#10 MODEL PLAY

Jahan Dotson

Receiving yards

WIN

OVER 23.5

fanduel -114

Projection 42.5

Proj. gap +19.0

Model win 61.6%

No-vig market 50.0%

No-vig edge +11.6%

Model-implied EV +15.6%

WHY THIS PLAY

Projection 42.5 is 19.0 above the 23.5 line.

Model win probability 61.6% vs 50.0% no-vig market probability creates a +11.6% edge.

Qualified with 2154 residual samples, 61.6% model win, +11.6% no-vig edge, and +15.6% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 87 receiving yards

#11 MODEL PLAY

Kalif Raymond

Receiving yards

LOSS

OVER 22.5

fanduel -114

Projection 39.9

Proj. gap +17.4

Model win 59.1%

No-vig market 50.0%

No-vig edge +9.1%

Model-implied EV +10.9%

WHY THIS PLAY

Projection 39.9 is 17.4 above the 22.5 line.

Model win probability 59.1% vs 50.0% no-vig market probability creates a +9.1% edge.

Qualified with 2154 residual samples, 59.1% model win, +9.1% no-vig edge, and +10.9% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 2154

Final: 18 receiving yards

#12 MODEL PLAY

Caleb Williams

Passing yards

WIN

OVER 219.5

fanduel -114

Projection 244.6

Proj. gap +25.1

Model win 58.9%

No-vig market 50.0%

No-vig edge +8.9%

Model-implied EV +10.6%

WHY THIS PLAY

Projection 244.6 is 25.1 above the 219.5 line.

Model win probability 58.9% vs 50.0% no-vig market probability creates a +8.9% edge.

Qualified with 516 residual samples, 58.9% model win, +8.9% no-vig edge, and +10.6% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.

Historical residual sample: 516

Final: 305 passing yards

#13 MODEL PLAY

Luther Burden III

Receiving yards

WIN

OVER 47.5

fanduel -114

Projection 64.1

Proj. gap +16.6

Model win 57.9%

Receiving yards

Did not qualify

Model side: OVER 41.5

fanduel -114

Projection47.5

Proj. gap+6.0

Model win41.2%

No-vig market50.0%

No-vig edge-8.8%

Model-implied EV-22.7%

Why it did not qualify: Model win probability did not clear the publication floor.

Historical residual sample: 2154